Overview

Dataset statistics

Number of variables80
Number of observations2000
Missing cells28
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 MiB
Average record size in memory640.1 B

Variable types

CAT55
NUM24
BOOL1

Warnings

Utilities has constant value "2000" Constant
Lot.Frontage has a high cardinality: 121 distinct values High cardinality
Mas.Vnr.Area has a high cardinality: 363 distinct values High cardinality
BsmtFin.SF.1 has a high cardinality: 817 distinct values High cardinality
BsmtFin.SF.2 has a high cardinality: 212 distinct values High cardinality
Bsmt.Unf.SF has a high cardinality: 928 distinct values High cardinality
Total.Bsmt.SF has a high cardinality: 871 distinct values High cardinality
Garage.Yr.Blt has a high cardinality: 101 distinct values High cardinality
Garage.Area has a high cardinality: 531 distinct values High cardinality
Misc.Val is highly skewed (γ1 = 24.8772176) Skewed
X2nd.Flr.SF has 1150 (57.5%) zeros Zeros
Low.Qual.Fin.SF has 1973 (98.7%) zeros Zeros
Fireplaces has 980 (49.0%) zeros Zeros
Wood.Deck.SF has 1064 (53.2%) zeros Zeros
Open.Porch.SF has 901 (45.1%) zeros Zeros
Enclosed.Porch has 1678 (83.9%) zeros Zeros
X3Ssn.Porch has 1977 (98.9%) zeros Zeros
Screen.Porch has 1824 (91.2%) zeros Zeros
Pool.Area has 1989 (99.5%) zeros Zeros
Misc.Val has 1928 (96.4%) zeros Zeros

Reproduction

Analysis started2020-11-20 08:52:55.491346
Analysis finished2020-11-20 08:55:45.752167
Duration2 minutes and 50.26 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

MS.SubClass
Real number (ℝ≥0)

Distinct16
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean56.945
Minimum20
Maximum190
Zeros0
Zeros (%)0.0%
Memory size15.6 KiB
2020-11-20T09:55:45.880239image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile20
Q120
median50
Q370
95-th percentile160
Maximum190
Range170
Interquartile range (IQR)50

Descriptive statistics

Standard deviation42.6992809
Coefficient of variation (CV)0.749833715
Kurtosis1.524778905
Mean56.945
Median Absolute Deviation (MAD)30
Skewness1.397445894
Sum113890
Variance1823.228589
MonotocityNot monotonic
2020-11-20T09:55:46.025146image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%) 
2075437.7%
 
6039019.5%
 
501979.8%
 
1201165.8%
 
70904.5%
 
30864.3%
 
160854.2%
 
90804.0%
 
80763.8%
 
190432.1%
 
Other values (6)834.2%
 
ValueCountFrequency (%) 
2075437.7%
 
30864.3%
 
4030.1%
 
45140.7%
 
501979.8%
 
ValueCountFrequency (%) 
190432.1%
 
180150.8%
 
160854.2%
 
15010.1%
 
1201165.8%
 

MS.Zoning
Categorical

Distinct7
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
RL
1549 
RM
317 
FV
 
103
RH
 
16
C (all)
 
13
Other values (2)
 
2
ValueCountFrequency (%) 
RL154977.5%
 
RM31715.8%
 
FV1035.1%
 
RH160.8%
 
C (all)130.7%
 
A (agr)10.1%
 
I (all)10.1%
 
2020-11-20T09:55:46.203988image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique2 ?
Unique (%)0.1%
2020-11-20T09:55:46.325590image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:46.488751image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length7
Median length2
Mean length2.0375
Min length2

Lot.Frontage
Categorical

HIGH CARDINALITY

Distinct121
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
None
334 
60
183 
80
 
97
70
 
95
50
 
83
Other values (116)
1208 
ValueCountFrequency (%) 
None33416.7%
 
601839.2%
 
80974.9%
 
70954.8%
 
50834.2%
 
75753.8%
 
65693.5%
 
85542.7%
 
64371.8%
 
63351.8%
 
Other values (111)93846.9%
 
2020-11-20T09:55:46.691441image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique21 ?
Unique (%)1.1%
2020-11-20T09:55:46.909302image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length2
Mean length2.3975
Min length2

Lot.Area
Real number (ℝ≥0)

Distinct1424
Distinct (%)71.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10296.665
Minimum1300
Maximum215245
Zeros0
Zeros (%)0.0%
Memory size15.6 KiB
2020-11-20T09:55:47.210222image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1300
5-th percentile3499
Q17500
median9465
Q311500
95-th percentile17227.75
Maximum215245
Range213945
Interquartile range (IQR)4000

Descriptive statistics

Standard deviation8828.208491
Coefficient of variation (CV)0.8573852302
Kurtosis243.6904132
Mean10296.665
Median Absolute Deviation (MAD)1992.5
Skewness12.94853691
Sum20593330
Variance77937265.16
MonotocityNot monotonic
2020-11-20T09:55:47.490488image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
9600331.7%
 
7200241.2%
 
6000231.1%
 
9000221.1%
 
10800190.9%
 
7500130.7%
 
6240130.7%
 
8400120.6%
 
6120120.6%
 
9100110.5%
 
Other values (1414)181890.9%
 
ValueCountFrequency (%) 
130010.1%
 
147010.1%
 
147610.1%
 
147710.1%
 
148410.1%
 
ValueCountFrequency (%) 
21524510.1%
 
16466010.1%
 
15900010.1%
 
11514910.1%
 
6388710.1%
 

Street
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
Pave
1992 
Grvl
 
8
ValueCountFrequency (%) 
Pave199299.6%
 
Grvl80.4%
 
2020-11-20T09:55:47.770548image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-20T09:55:47.925378image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:48.051135image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length4
Mean length4
Min length4

Alley
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
None
1865 
Grvl
 
85
Pave
 
50
ValueCountFrequency (%) 
None186593.2%
 
Grvl854.2%
 
Pave502.5%
 
2020-11-20T09:55:48.281004image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-20T09:55:48.520821image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:48.752253image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length4
Mean length4
Min length4

Lot.Shape
Categorical

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
Reg
1275 
IR1
657 
IR2
 
55
IR3
 
13
ValueCountFrequency (%) 
Reg127563.7%
 
IR165732.9%
 
IR2552.8%
 
IR3130.7%
 
2020-11-20T09:55:49.041496image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-20T09:55:49.360335image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:49.574872image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

Land.Contour
Categorical

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
Lvl
1809 
Bnk
 
75
HLS
 
74
Low
 
42
ValueCountFrequency (%) 
Lvl180990.5%
 
Bnk753.8%
 
HLS743.7%
 
Low422.1%
 
2020-11-20T09:55:49.759426image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-20T09:55:49.944793image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:50.080651image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

Utilities
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
AllPub
2000 
ValueCountFrequency (%) 
AllPub2000100.0%
 
2020-11-20T09:55:50.232072image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-20T09:55:50.336297image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:50.441833image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length6
Mean length6
Min length6

Lot.Config
Categorical

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
Inside
1452 
Corner
344 
CulDSac
 
129
FR2
 
61
FR3
 
14
ValueCountFrequency (%) 
Inside145272.6%
 
Corner34417.2%
 
CulDSac1296.5%
 
FR2613.0%
 
FR3140.7%
 
2020-11-20T09:55:50.604255image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-20T09:55:50.723863image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:50.877901image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length7
Median length6
Mean length5.952
Min length3

Land.Slope
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
Gtl
1900 
Mod
 
86
Sev
 
14
ValueCountFrequency (%) 
Gtl190095.0%
 
Mod864.3%
 
Sev140.7%
 
2020-11-20T09:55:51.058978image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-20T09:55:51.173226image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:51.293559image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

Neighborhood
Categorical

Distinct27
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
Nonemes
303 
CollgCr
192 
OldTown
166 
Edwards
134 
Somerst
134 
Other values (22)
1071 
ValueCountFrequency (%) 
Nonemes30315.2%
 
CollgCr1929.6%
 
OldTown1668.3%
 
Edwards1346.7%
 
Somerst1346.7%
 
Sawyer1075.3%
 
NridgHt1045.2%
 
Gilbert995.0%
 
NWAmes924.6%
 
SawyerW804.0%
 
Other values (17)58929.4%
 
2020-11-20T09:55:51.473877image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-11-20T09:55:51.664787image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length7
Median length7
Mean length6.8055
Min length5

Condition.1
Categorical

Distinct9
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
Norm
1721 
Feedr
 
113
Artery
 
61
RRAn
 
33
PosN
 
25
Other values (4)
 
47
ValueCountFrequency (%) 
Norm172186.1%
 
Feedr1135.7%
 
Artery613.0%
 
RRAn331.7%
 
PosN251.2%
 
RRAe201.0%
 
PosA140.7%
 
RRNn80.4%
 
RRNe50.2%
 
2020-11-20T09:55:51.851017image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-20T09:55:51.976981image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:52.170950image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length4
Mean length4.1175
Min length4

Condition.2
Categorical

Distinct7
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
Norm
1981 
Feedr
 
9
PosN
 
3
Artery
 
3
RRNn
 
2
Other values (2)
 
2
ValueCountFrequency (%) 
Norm198199.1%
 
Feedr90.4%
 
PosN30.1%
 
Artery30.1%
 
RRNn20.1%
 
PosA10.1%
 
RRAn10.1%
 
2020-11-20T09:55:52.358870image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique2 ?
Unique (%)0.1%
2020-11-20T09:55:53.006803image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:53.182218image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length4
Mean length4.0075
Min length4

Bldg.Type
Categorical

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
1Fam
1665 
TwnhsE
 
150
Duplex
 
80
Twnhs
 
61
2fmCon
 
44
ValueCountFrequency (%) 
1Fam166583.2%
 
TwnhsE1507.5%
 
Duplex804.0%
 
Twnhs613.0%
 
2fmCon442.2%
 
2020-11-20T09:55:53.371829image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-20T09:55:53.496894image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:53.654865image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length4
Mean length4.3045
Min length4

House.Style
Categorical

Distinct8
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
1Story
1010 
2Story
595 
1.5Fin
216 
SLvl
 
84
SFoyer
 
64
Other values (3)
 
31
ValueCountFrequency (%) 
1Story101050.5%
 
2Story59529.8%
 
1.5Fin21610.8%
 
SLvl844.2%
 
SFoyer643.2%
 
2.5Unf140.7%
 
1.5Unf140.7%
 
2.5Fin30.1%
 
2020-11-20T09:55:53.827602image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-20T09:55:53.938052image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:54.124879image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length6
Mean length5.916
Min length4

Overall.Qual
Real number (ℝ≥0)

Distinct10
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.082
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size15.6 KiB
2020-11-20T09:55:54.281761image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q15
median6
Q37
95-th percentile8
Maximum10
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.387169103
Coefficient of variation (CV)0.2280777873
Kurtosis-0.0586251189
Mean6.082
Median Absolute Deviation (MAD)1
Skewness0.1862205748
Sum12164
Variance1.924238119
MonotocityNot monotonic
2020-11-20T09:55:54.413005image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
558029.0%
 
650325.1%
 
739219.6%
 
825412.7%
 
41527.6%
 
9703.5%
 
3241.2%
 
10140.7%
 
290.4%
 
120.1%
 
ValueCountFrequency (%) 
120.1%
 
290.4%
 
3241.2%
 
41527.6%
 
558029.0%
 
ValueCountFrequency (%) 
10140.7%
 
9703.5%
 
825412.7%
 
739219.6%
 
650325.1%
 

Overall.Cond
Real number (ℝ≥0)

Distinct9
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.574
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size15.6 KiB
2020-11-20T09:55:54.554836image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q15
median5
Q36
95-th percentile8
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.105502179
Coefficient of variation (CV)0.1983319302
Kurtosis1.447757114
Mean5.574
Median Absolute Deviation (MAD)0
Skewness0.5762708204
Sum11148
Variance1.222135068
MonotocityNot monotonic
2020-11-20T09:55:54.691637image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%) 
5111055.5%
 
638019.0%
 
726813.4%
 
8995.0%
 
4743.7%
 
3321.6%
 
9271.4%
 
250.2%
 
150.2%
 
ValueCountFrequency (%) 
150.2%
 
250.2%
 
3321.6%
 
4743.7%
 
5111055.5%
 
ValueCountFrequency (%) 
9271.4%
 
8995.0%
 
726813.4%
 
638019.0%
 
5111055.5%
 

Year.Built
Real number (ℝ≥0)

Distinct112
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1971.0795
Minimum1872
Maximum2010
Zeros0
Zeros (%)0.0%
Memory size15.6 KiB
2020-11-20T09:55:54.868854image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1872
5-th percentile1916
Q11954
median1972
Q32000
95-th percentile2007
Maximum2010
Range138
Interquartile range (IQR)46

Descriptive statistics

Standard deviation29.9854255
Coefficient of variation (CV)0.01521269208
Kurtosis-0.489327299
Mean1971.0795
Median Absolute Deviation (MAD)25
Skewness-0.5862925444
Sum3942159
Variance899.1257426
MonotocityNot monotonic
2020-11-20T09:55:55.059432image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
2005954.8%
 
2006894.5%
 
2007733.6%
 
2004663.3%
 
2003582.9%
 
1977391.9%
 
1920391.9%
 
1998381.9%
 
1958371.8%
 
1999361.8%
 
Other values (102)143071.5%
 
ValueCountFrequency (%) 
187210.1%
 
187910.1%
 
188040.2%
 
188510.1%
 
189050.2%
 
ValueCountFrequency (%) 
201020.1%
 
2009160.8%
 
2008341.7%
 
2007733.6%
 
2006894.5%
 

Year.Remod.Add
Real number (ℝ≥0)

Distinct61
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1984.0135
Minimum1950
Maximum2010
Zeros0
Zeros (%)0.0%
Memory size15.6 KiB
2020-11-20T09:55:55.256627image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1950
5-th percentile1950
Q11965
median1993
Q32004
95-th percentile2007
Maximum2010
Range60
Interquartile range (IQR)39

Descriptive statistics

Standard deviation20.88177056
Coefficient of variation (CV)0.01052501435
Kurtosis-1.365790876
Mean1984.0135
Median Absolute Deviation (MAD)14
Skewness-0.4280258359
Sum3968027
Variance436.0483419
MonotocityNot monotonic
2020-11-20T09:55:55.449532image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
195024612.3%
 
20061397.0%
 
20071085.4%
 
2005924.6%
 
2004783.9%
 
2003653.2%
 
2000603.0%
 
1998582.9%
 
2002562.8%
 
2008552.8%
 
Other values (51)104352.1%
 
ValueCountFrequency (%) 
195024612.3%
 
1951100.5%
 
195280.4%
 
1953160.8%
 
1954201.0%
 
ValueCountFrequency (%) 
201080.4%
 
2009241.2%
 
2008552.8%
 
20071085.4%
 
20061397.0%
 

Roof.Style
Categorical

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
Gable
1580 
Hip
381 
Flat
 
17
Gambrel
 
15
Mansard
 
5
ValueCountFrequency (%) 
Gable158079.0%
 
Hip38119.1%
 
Flat170.9%
 
Gambrel150.8%
 
Mansard50.2%
 
Shed20.1%
 
2020-11-20T09:55:55.653651image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-20T09:55:55.777754image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:55.946143image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length7
Median length5
Mean length4.6295
Min length3

Roof.Matl
Categorical

Distinct7
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
CompShg
1967 
Tar&Grv
 
18
WdShake
 
7
WdShngl
 
5
ClyTile
 
1
Other values (2)
 
2
ValueCountFrequency (%) 
CompShg196798.4%
 
Tar&Grv180.9%
 
WdShake70.4%
 
WdShngl50.2%
 
ClyTile10.1%
 
Membran10.1%
 
Metal10.1%
 
2020-11-20T09:55:56.128976image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique3 ?
Unique (%)0.1%
2020-11-20T09:55:56.250523image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:56.424754image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length7
Median length7
Mean length6.999
Min length5

Exterior.1st
Categorical

Distinct14
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
VinylSd
686 
MetalSd
308 
HdBoard
297 
Wd Sdng
287 
Plywood
157 
Other values (9)
265 
ValueCountFrequency (%) 
VinylSd68634.3%
 
MetalSd30815.4%
 
HdBoard29714.8%
 
Wd Sdng28714.3%
 
Plywood1577.8%
 
CemntBd864.3%
 
BrkFace673.4%
 
WdShing402.0%
 
Stucco311.6%
 
AsbShng311.6%
 
Other values (4)100.5%
 
2020-11-20T09:55:56.613614image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-11-20T09:55:56.798121image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length7
Median length7
Mean length6.9825
Min length5

Exterior.2nd
Categorical

Distinct16
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
VinylSd
681 
MetalSd
308 
Wd Sdng
275 
HdBoard
269 
Plywood
195 
Other values (11)
272 
ValueCountFrequency (%) 
VinylSd68134.1%
 
MetalSd30815.4%
 
Wd Sdng27513.8%
 
HdBoard26913.5%
 
Plywood1959.8%
 
CmentBd844.2%
 
Wd Shng532.6%
 
BrkFace371.8%
 
Stucco351.8%
 
AsbShng271.4%
 
Other values (6)361.8%
 
2020-11-20T09:55:56.981112image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-11-20T09:55:57.158833image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length7
Median length7
Mean length6.975
Min length5

Mas.Vnr.Type
Categorical

Distinct5
Distinct (%)0.3%
Missing16
Missing (%)0.8%
Memory size15.6 KiB
None
1216 
BrkFace
593 
Stone
159 
BrkCmn
 
15
CBlock
 
1
ValueCountFrequency (%) 
None121660.8%
 
BrkFace59329.6%
 
Stone1598.0%
 
BrkCmn150.8%
 
CBlock10.1%
 
(Missing)160.8%
 
2020-11-20T09:55:57.333943image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)0.1%
2020-11-20T09:55:57.446492image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:57.597229image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length7
Median length4
Mean length4.977
Min length3

Mas.Vnr.Area
Categorical

HIGH CARDINALITY

Distinct363
Distinct (%)18.1%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
0
1215 
None
 
16
120
 
10
72
 
9
108
 
9
Other values (358)
741 
ValueCountFrequency (%) 
0121560.8%
 
None160.8%
 
120100.5%
 
7290.4%
 
10890.4%
 
17690.4%
 
21690.4%
 
18080.4%
 
14480.4%
 
8080.4%
 
Other values (353)69934.9%
 
2020-11-20T09:55:57.807348image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique195 ?
Unique (%)9.8%
2020-11-20T09:55:57.996774image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length1
Mean length1.728
Min length1

Exter.Qual
Categorical

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
TA
1230 
Gd
683 
Ex
 
66
Fa
 
21
ValueCountFrequency (%) 
TA123061.5%
 
Gd68334.2%
 
Ex663.3%
 
Fa211.1%
 
2020-11-20T09:55:58.181224image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-20T09:55:58.296959image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:58.425989image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length2
Median length2
Mean length2
Min length2

Exter.Cond
Categorical

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
TA
1734 
Gd
218 
Fa
 
40
Ex
 
8
ValueCountFrequency (%) 
TA173486.7%
 
Gd21810.9%
 
Fa402.0%
 
Ex80.4%
 
2020-11-20T09:55:58.588398image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-20T09:55:58.700088image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:58.827765image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length2
Median length2
Mean length2
Min length2

Foundation
Categorical

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
PConc
873 
CBlock
867 
BrkTil
215 
Slab
 
34
Stone
 
7
ValueCountFrequency (%) 
PConc87343.6%
 
CBlock86743.4%
 
BrkTil21510.8%
 
Slab341.7%
 
Stone70.4%
 
Wood40.2%
 
2020-11-20T09:55:58.981536image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-20T09:55:59.090953image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:59.295786image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length6
Mean length5.522
Min length4

Bsmt.Qual
Categorical

Distinct6
Distinct (%)0.3%
Missing1
Missing (%)< 0.1%
Memory size15.6 KiB
TA
892 
Gd
837 
Ex
163 
Fa
 
54
None
 
52
ValueCountFrequency (%) 
TA89244.6%
 
Gd83741.9%
 
Ex1638.2%
 
Fa542.7%
 
None522.6%
 
Po10.1%
 
(Missing)10.1%
 
2020-11-20T09:55:59.506974image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)0.1%
2020-11-20T09:55:59.613956image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:59.780977image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length2
Mean length2.0525
Min length2

Bsmt.Cond
Categorical

Distinct6
Distinct (%)0.3%
Missing1
Missing (%)< 0.1%
Memory size15.6 KiB
TA
1783 
Gd
 
88
Fa
 
71
None
 
52
Ex
 
3
ValueCountFrequency (%) 
TA178389.1%
 
Gd884.4%
 
Fa713.5%
 
None522.6%
 
Ex30.1%
 
Po20.1%
 
(Missing)10.1%
 
2020-11-20T09:55:59.967211image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-20T09:56:00.102753image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:56:00.267895image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length2
Mean length2.0525
Min length2

Bsmt.Exposure
Categorical

Distinct5
Distinct (%)0.3%
Missing3
Missing (%)0.1%
Memory size15.6 KiB
No
1306 
Av
285 
Gd
188 
Mn
166 
None
 
52
ValueCountFrequency (%) 
No130665.3%
 
Av28514.2%
 
Gd1889.4%
 
Mn1668.3%
 
None522.6%
 
(Missing)30.1%
 
2020-11-20T09:56:00.450523image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-20T09:56:00.564690image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:56:00.718005image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length2
Mean length2.0535
Min length2

BsmtFin.Type.1
Categorical

Distinct7
Distinct (%)0.4%
Missing1
Missing (%)< 0.1%
Memory size15.6 KiB
GLQ
584 
Unf
565 
ALQ
293 
Rec
204 
BLQ
195 
Other values (2)
158 
ValueCountFrequency (%) 
GLQ58429.2%
 
Unf56528.2%
 
ALQ29314.6%
 
Rec20410.2%
 
BLQ1959.8%
 
LwQ1065.3%
 
None522.6%
 
(Missing)10.1%
 
2020-11-20T09:56:00.898043image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-20T09:56:01.016306image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:56:01.181927image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length3
Mean length3.026
Min length3

BsmtFin.SF.1
Categorical

HIGH CARDINALITY

Distinct817
Distinct (%)40.8%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
0
617 
24
 
21
16
 
9
20
 
8
500
 
7
Other values (812)
1338 
ValueCountFrequency (%) 
061730.9%
 
24211.1%
 
1690.4%
 
2080.4%
 
50070.4%
 
62470.4%
 
62560.3%
 
46860.3%
 
56060.3%
 
93660.3%
 
Other values (807)130765.3%
 
2020-11-20T09:56:01.391198image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique487 ?
Unique (%)24.3%
2020-11-20T09:56:01.581255image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length3
Mean length2.458
Min length1

BsmtFin.Type.2
Categorical

Distinct7
Distinct (%)0.4%
Missing2
Missing (%)0.1%
Memory size15.6 KiB
Unf
1694 
Rec
 
70
LwQ
 
67
None
 
52
BLQ
 
50
Other values (2)
 
65
ValueCountFrequency (%) 
Unf169484.7%
 
Rec703.5%
 
LwQ673.4%
 
None522.6%
 
BLQ502.5%
 
ALQ381.9%
 
GLQ271.4%
 
(Missing)20.1%
 
2020-11-20T09:56:01.747198image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-20T09:56:01.865483image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:56:02.030489image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length3
Mean length3.026
Min length3

BsmtFin.SF.2
Categorical

HIGH CARDINALITY

Distinct212
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
0
1746 
180
 
4
144
 
3
435
 
3
147
 
3
Other values (207)
241 
ValueCountFrequency (%) 
0174687.3%
 
18040.2%
 
14430.1%
 
43530.1%
 
14730.1%
 
29430.1%
 
25220.1%
 
10520.1%
 
6020.1%
 
29020.1%
 
Other values (202)23011.5%
 
2020-11-20T09:56:02.239392image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique174 ?
Unique (%)8.7%
2020-11-20T09:56:02.440446image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length1
Mean length1.2475
Min length1

Bsmt.Unf.SF
Categorical

HIGH CARDINALITY

Distinct928
Distinct (%)46.4%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
0
 
170
384
 
13
672
 
10
768
 
9
270
 
9
Other values (923)
1789 
ValueCountFrequency (%) 
01708.5%
 
384130.7%
 
672100.5%
 
76890.4%
 
27090.4%
 
10090.4%
 
72890.4%
 
81680.4%
 
39680.4%
 
62480.4%
 
Other values (918)174787.4%
 
2020-11-20T09:56:02.641801image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique475 ?
Unique (%)23.8%
2020-11-20T09:56:02.832951image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length3
Mean length2.9405
Min length1

Total.Bsmt.SF
Categorical

HIGH CARDINALITY

Distinct871
Distinct (%)43.5%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
864
 
56
0
 
52
672
 
23
1040
 
22
768
 
21
Other values (866)
1826 
ValueCountFrequency (%) 
864562.8%
 
0522.6%
 
672231.1%
 
1040221.1%
 
768211.1%
 
912190.9%
 
816140.7%
 
1008130.7%
 
960120.6%
 
780120.6%
 
Other values (861)175687.8%
 
2020-11-20T09:56:03.032988image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique458 ?
Unique (%)22.9%
2020-11-20T09:56:03.223489image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length3
Mean length3.444
Min length1

Heating
Categorical

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
GasA
1968 
GasW
 
20
Grav
 
5
Wall
 
4
OthW
 
2
ValueCountFrequency (%) 
GasA196898.4%
 
GasW201.0%
 
Grav50.2%
 
Wall40.2%
 
OthW20.1%
 
Floor10.1%
 
2020-11-20T09:56:03.405610image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-11-20T09:56:03.524867image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:56:03.676644image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length5
Median length4
Mean length4.0005
Min length4

Heating.QC
Categorical

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
Ex
1012 
TA
613 
Gd
313 
Fa
 
61
Po
 
1
ValueCountFrequency (%) 
Ex101250.6%
 
TA61330.6%
 
Gd31315.7%
 
Fa613.0%
 
Po10.1%
 
2020-11-20T09:56:03.848362image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-11-20T09:56:03.960682image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:56:04.101676image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length2
Median length2
Mean length2
Min length2
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
Y
1873 
N
 
127
ValueCountFrequency (%) 
Y187393.7%
 
N1276.3%
 
2020-11-20T09:56:04.221397image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Electrical
Categorical

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
SBrkr
1837 
FuseA
 
122
FuseF
 
37
FuseP
 
4
ValueCountFrequency (%) 
SBrkr183791.8%
 
FuseA1226.1%
 
FuseF371.8%
 
FuseP40.2%
 
2020-11-20T09:56:04.338062image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-20T09:56:04.449144image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:56:04.580698image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length5
Median length5
Mean length5
Min length5

X1st.Flr.SF
Real number (ℝ≥0)

Distinct902
Distinct (%)45.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1158.7155
Minimum407
Maximum4692
Zeros0
Zeros (%)0.0%
Memory size15.6 KiB
2020-11-20T09:56:04.749185image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum407
5-th percentile672
Q1877.75
median1088
Q31391.25
95-th percentile1816.3
Maximum4692
Range4285
Interquartile range (IQR)513.5

Descriptive statistics

Standard deviation379.7010153
Coefficient of variation (CV)0.3276913231
Kurtosis4.077817611
Mean1158.7155
Median Absolute Deviation (MAD)240
Skewness1.142521982
Sum2317431
Variance144172.861
MonotocityNot monotonic
2020-11-20T09:56:04.925473image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
864381.9%
 
1040241.2%
 
912130.7%
 
960120.6%
 
936120.6%
 
546120.6%
 
768110.5%
 
894110.5%
 
672110.5%
 
816100.5%
 
Other values (892)184692.3%
 
ValueCountFrequency (%) 
40710.1%
 
44210.1%
 
44810.1%
 
45310.1%
 
48010.1%
 
ValueCountFrequency (%) 
469210.1%
 
272610.1%
 
269610.1%
 
267410.1%
 
255210.1%
 

X2nd.Flr.SF
Real number (ℝ≥0)

ZEROS

Distinct500
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean334.3805
Minimum0
Maximum2065
Zeros1150
Zeros (%)57.5%
Memory size15.6 KiB
2020-11-20T09:56:05.117452image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3703.25
95-th percentile1133.05
Maximum2065
Range2065
Interquartile range (IQR)703.25

Descriptive statistics

Standard deviation427.5199731
Coefficient of variation (CV)1.278543375
Kurtosis-0.5125040066
Mean334.3805
Median Absolute Deviation (MAD)0
Skewness0.8479014729
Sum668761
Variance182773.3274
MonotocityNot monotonic
2020-11-20T09:56:05.308997image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0115057.5%
 
546170.9%
 
728120.6%
 
60080.4%
 
89680.4%
 
67280.4%
 
88680.4%
 
50470.4%
 
78070.4%
 
75460.3%
 
Other values (490)76938.5%
 
ValueCountFrequency (%) 
0115057.5%
 
12510.1%
 
16710.1%
 
18010.1%
 
18210.1%
 
ValueCountFrequency (%) 
206510.1%
 
187210.1%
 
181810.1%
 
178810.1%
 
162910.1%
 

Low.Qual.Fin.SF
Real number (ℝ≥0)

ZEROS

Distinct25
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.379
Minimum0
Maximum697
Zeros1973
Zeros (%)98.7%
Memory size15.6 KiB
2020-11-20T09:56:05.481370image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum697
Range697
Interquartile range (IQR)0

Descriptive statistics

Standard deviation42.55573821
Coefficient of variation (CV)9.718140719
Kurtosis124.2883137
Mean4.379
Median Absolute Deviation (MAD)0
Skewness10.83882085
Sum8758
Variance1810.990854
MonotocityNot monotonic
2020-11-20T09:56:05.649288image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%) 
0197398.7%
 
8030.1%
 
20520.1%
 
36210.1%
 
5310.1%
 
10810.1%
 
14010.1%
 
14410.1%
 
15610.1%
 
25910.1%
 
Other values (15)150.8%
 
ValueCountFrequency (%) 
0197398.7%
 
5310.1%
 
8030.1%
 
10810.1%
 
14010.1%
 
ValueCountFrequency (%) 
69710.1%
 
52810.1%
 
51510.1%
 
51410.1%
 
51210.1%
 

Gr.Liv.Area
Real number (ℝ≥0)

Distinct1051
Distinct (%)52.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1497.475
Minimum407
Maximum5642
Zeros0
Zeros (%)0.0%
Memory size15.6 KiB
2020-11-20T09:56:05.836666image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum407
5-th percentile864
Q11126.75
median1447.5
Q31734
95-th percentile2473.1
Maximum5642
Range5235
Interquartile range (IQR)607.25

Descriptive statistics

Standard deviation498.5617186
Coefficient of variation (CV)0.3329349195
Kurtosis3.762152569
Mean1497.475
Median Absolute Deviation (MAD)307.5
Skewness1.195519652
Sum2994950
Variance248563.7873
MonotocityNot monotonic
2020-11-20T09:56:06.038167image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
864321.6%
 
1040211.1%
 
1092170.9%
 
1200130.7%
 
1456130.7%
 
1728100.5%
 
912100.5%
 
89490.4%
 
130280.4%
 
84880.4%
 
Other values (1041)185993.0%
 
ValueCountFrequency (%) 
40710.1%
 
48010.1%
 
49210.1%
 
49810.1%
 
52010.1%
 
ValueCountFrequency (%) 
564210.1%
 
447610.1%
 
431610.1%
 
350010.1%
 
349310.1%
 

Bsmt.Full.Bath
Categorical

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
0
1154 
1
818 
2
 
26
3
 
1
None
 
1
ValueCountFrequency (%) 
0115457.7%
 
181840.9%
 
2261.3%
 
310.1%
 
None10.1%
 
2020-11-20T09:56:06.224865image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique2 ?
Unique (%)0.1%
2020-11-20T09:56:06.335787image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:56:06.478713image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length1
Mean length1.0015
Min length1

Bsmt.Half.Bath
Categorical

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
0
1870 
1
 
125
2
 
4
None
 
1
ValueCountFrequency (%) 
0187093.5%
 
11256.2%
 
240.2%
 
None10.1%
 
2020-11-20T09:56:06.653644image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-11-20T09:56:06.764093image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:56:06.897936image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length1
Mean length1.0015
Min length1

Full.Bath
Real number (ℝ≥0)

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5625
Minimum0
Maximum4
Zeros10
Zeros (%)0.5%
Memory size15.6 KiB
2020-11-20T09:56:07.043204image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q32
95-th percentile2
Maximum4
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.5515848737
Coefficient of variation (CV)0.3530143192
Kurtosis-0.7520980827
Mean1.5625
Median Absolute Deviation (MAD)0
Skewness0.1095884932
Sum3125
Variance0.3042458729
MonotocityNot monotonic
2020-11-20T09:56:07.178957image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
2104252.1%
 
190245.1%
 
3452.2%
 
0100.5%
 
410.1%
 
ValueCountFrequency (%) 
0100.5%
 
190245.1%
 
2104252.1%
 
3452.2%
 
410.1%
 
ValueCountFrequency (%) 
410.1%
 
3452.2%
 
2104252.1%
 
190245.1%
 
0100.5%
 

Half.Bath
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
0
1272 
1
710 
2
 
18
ValueCountFrequency (%) 
0127263.6%
 
171035.5%
 
2180.9%
 
2020-11-20T09:56:07.344244image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-20T09:56:07.446502image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:56:07.563504image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

Bedroom.AbvGr
Real number (ℝ≥0)

Distinct8
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.8715
Minimum0
Maximum8
Zeros6
Zeros (%)0.3%
Memory size15.6 KiB
2020-11-20T09:56:07.706507image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q12
median3
Q33
95-th percentile4
Maximum8
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.8278468549
Coefficient of variation (CV)0.2882977033
Kurtosis2.241736373
Mean2.8715
Median Absolute Deviation (MAD)0
Skewness0.3436634193
Sum5743
Variance0.6853304152
MonotocityNot monotonic
2020-11-20T09:56:07.845836image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
3111255.6%
 
248524.2%
 
427513.8%
 
1733.6%
 
5321.6%
 
6160.8%
 
060.3%
 
810.1%
 
ValueCountFrequency (%) 
060.3%
 
1733.6%
 
248524.2%
 
3111255.6%
 
427513.8%
 
ValueCountFrequency (%) 
810.1%
 
6160.8%
 
5321.6%
 
427513.8%
 
3111255.6%
 

Kitchen.AbvGr
Categorical

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
1
1902 
2
 
94
0
 
3
3
 
1
ValueCountFrequency (%) 
1190295.1%
 
2944.7%
 
030.1%
 
310.1%
 
2020-11-20T09:56:08.015703image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-11-20T09:56:08.130949image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:56:08.261781image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

Kitchen.Qual
Categorical

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
TA
1025 
Gd
785 
Ex
140 
Fa
 
50
ValueCountFrequency (%) 
TA102551.2%
 
Gd78539.2%
 
Ex1407.0%
 
Fa502.5%
 
2020-11-20T09:56:08.417686image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-20T09:56:08.522569image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:56:08.652547image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length2
Median length2
Mean length2
Min length2

TotRms.AbvGrd
Real number (ℝ≥0)

Distinct11
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.4475
Minimum3
Maximum14
Zeros0
Zeros (%)0.0%
Memory size15.6 KiB
2020-11-20T09:56:08.792052image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile4
Q15
median6
Q37
95-th percentile9
Maximum14
Range11
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.569227513
Coefficient of variation (CV)0.2433854227
Kurtosis0.8147935601
Mean6.4475
Median Absolute Deviation (MAD)1
Skewness0.6981321697
Sum12895
Variance2.462474987
MonotocityNot monotonic
2020-11-20T09:56:08.929159image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%) 
657428.7%
 
743221.6%
 
540420.2%
 
824012.0%
 
41386.9%
 
91045.2%
 
10582.9%
 
11211.1%
 
3180.9%
 
12100.5%
 
ValueCountFrequency (%) 
3180.9%
 
41386.9%
 
540420.2%
 
657428.7%
 
743221.6%
 
ValueCountFrequency (%) 
1410.1%
 
12100.5%
 
11211.1%
 
10582.9%
 
91045.2%
 

Functional
Categorical

Distinct7
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
Typ
1868 
Min2
 
45
Min1
 
44
Mod
 
23
Maj1
 
13
Other values (2)
 
7
ValueCountFrequency (%) 
Typ186893.4%
 
Min2452.2%
 
Min1442.2%
 
Mod231.1%
 
Maj1130.7%
 
Maj250.2%
 
Sev20.1%
 
2020-11-20T09:56:09.107232image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-20T09:56:09.243388image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:56:09.409076image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length3
Mean length3.0535
Min length3

Fireplaces
Real number (ℝ≥0)

ZEROS

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.596
Minimum0
Maximum4
Zeros980
Zeros (%)49.0%
Memory size15.6 KiB
2020-11-20T09:56:09.596652image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile2
Maximum4
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.6503810404
Coefficient of variation (CV)1.091243356
Kurtosis0.1273703751
Mean0.596
Median Absolute Deviation (MAD)1
Skewness0.7548478245
Sum1192
Variance0.4229954977
MonotocityNot monotonic
2020-11-20T09:56:09.733885image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
098049.0%
 
185742.9%
 
21557.8%
 
370.4%
 
410.1%
 
ValueCountFrequency (%) 
098049.0%
 
185742.9%
 
21557.8%
 
370.4%
 
410.1%
 
ValueCountFrequency (%) 
410.1%
 
370.4%
 
21557.8%
 
185742.9%
 
098049.0%
 

Fireplace.Qu
Categorical

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
None
980 
Gd
497 
TA
413 
Fa
 
51
Po
 
34
ValueCountFrequency (%) 
None98049.0%
 
Gd49724.9%
 
TA41320.6%
 
Fa512.5%
 
Po341.7%
 
Ex251.2%
 
2020-11-20T09:56:09.902005image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-20T09:56:10.011326image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:56:10.188236image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length2
Mean length2.98
Min length2

Garage.Type
Categorical

Distinct7
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
Attchd
1182 
Detchd
531 
BuiltIn
121 
None
 
110
Basment
 
28
Other values (2)
 
28
ValueCountFrequency (%) 
Attchd118259.1%
 
Detchd53126.6%
 
BuiltIn1216.0%
 
None1105.5%
 
Basment281.4%
 
2Types150.8%
 
CarPort130.7%
 
2020-11-20T09:56:10.359003image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-20T09:56:10.470750image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:56:10.639538image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length7
Median length6
Mean length5.971
Min length4

Garage.Yr.Blt
Categorical

HIGH CARDINALITY

Distinct101
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
None
 
112
2005
 
98
2006
 
79
2007
 
75
2004
 
66
Other values (96)
1570 
ValueCountFrequency (%) 
None1125.6%
 
2005984.9%
 
2006794.0%
 
2007753.8%
 
2004663.3%
 
2003613.0%
 
1998482.4%
 
1977442.2%
 
2008391.9%
 
1993371.8%
 
Other values (91)134167.0%
 
2020-11-20T09:56:10.839940image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique8 ?
Unique (%)0.4%
2020-11-20T09:56:11.025844image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length4
Mean length4
Min length4

Garage.Finish
Categorical

Distinct4
Distinct (%)0.2%
Missing2
Missing (%)0.1%
Memory size15.6 KiB
Unf
831 
RFn
578 
Fin
479 
None
110 
ValueCountFrequency (%) 
Unf83141.5%
 
RFn57828.9%
 
Fin47923.9%
 
None1105.5%
 
(Missing)20.1%
 
2020-11-20T09:56:11.199884image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-20T09:56:11.320121image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:56:11.450194image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length3
Mean length3.055
Min length3

Garage.Cars
Categorical

Distinct7
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
2
1091 
1
537 
3
251 
0
110 
4
 
9
Other values (2)
 
2
ValueCountFrequency (%) 
2109154.5%
 
153726.9%
 
325112.6%
 
01105.5%
 
490.4%
 
510.1%
 
None10.1%
 
2020-11-20T09:56:11.613590image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique2 ?
Unique (%)0.1%
2020-11-20T09:56:11.729095image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:56:11.890747image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length1
Mean length1.0015
Min length1

Garage.Area
Categorical

HIGH CARDINALITY

Distinct531
Distinct (%)26.6%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
0
 
110
576
 
73
440
 
61
484
 
52
240
 
48
Other values (526)
1656 
ValueCountFrequency (%) 
01105.5%
 
576733.6%
 
440613.0%
 
484522.6%
 
240482.4%
 
480371.8%
 
288371.8%
 
528351.8%
 
400351.8%
 
308321.6%
 
Other values (521)148074.0%
 
2020-11-20T09:56:12.095151image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique236 ?
Unique (%)11.8%
2020-11-20T09:56:12.287162image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length3
Mean length2.9015
Min length1

Garage.Qual
Categorical

Distinct6
Distinct (%)0.3%
Missing1
Missing (%)< 0.1%
Memory size15.6 KiB
TA
1785 
None
 
111
Fa
 
84
Gd
 
16
Po
 
2
ValueCountFrequency (%) 
TA178589.2%
 
None1115.5%
 
Fa844.2%
 
Gd160.8%
 
Po20.1%
 
Ex10.1%
 
(Missing)10.1%
 
2020-11-20T09:56:12.455133image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)0.1%
2020-11-20T09:56:12.567948image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:56:12.727302image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length2
Mean length2.1115
Min length2

Garage.Cond
Categorical

Distinct6
Distinct (%)0.3%
Missing1
Missing (%)< 0.1%
Memory size15.6 KiB
TA
1816 
None
 
111
Fa
 
53
Gd
 
9
Po
 
8
ValueCountFrequency (%) 
TA181690.8%
 
None1115.5%
 
Fa532.6%
 
Gd90.4%
 
Po80.4%
 
Ex20.1%
 
(Missing)10.1%
 
2020-11-20T09:56:12.903100image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-20T09:56:13.016238image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:56:13.176740image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length2
Mean length2.1115
Min length2

Paved.Drive
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
Y
1809 
N
 
145
P
 
46
ValueCountFrequency (%) 
Y180990.5%
 
N1457.2%
 
P462.3%
 
2020-11-20T09:56:13.357432image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-20T09:56:13.471271image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:56:13.588487image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

Wood.Deck.SF
Real number (ℝ≥0)

ZEROS

Distinct324
Distinct (%)16.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean93.0585
Minimum0
Maximum870
Zeros1064
Zeros (%)53.2%
Memory size15.6 KiB
2020-11-20T09:56:13.758913image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3168
95-th percentile335
Maximum870
Range870
Interquartile range (IQR)168

Descriptive statistics

Standard deviation126.6331278
Coefficient of variation (CV)1.360790554
Kurtosis3.447389311
Mean93.0585
Median Absolute Deviation (MAD)0
Skewness1.624127014
Sum186117
Variance16035.94905
MonotocityNot monotonic
2020-11-20T09:56:13.942363image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0106453.2%
 
192472.4%
 
100432.1%
 
144422.1%
 
168351.8%
 
120351.8%
 
140170.9%
 
224130.7%
 
240130.7%
 
216120.6%
 
Other values (314)67934.0%
 
ValueCountFrequency (%) 
0106453.2%
 
1210.1%
 
1610.1%
 
2010.1%
 
2210.1%
 
ValueCountFrequency (%) 
87010.1%
 
85710.1%
 
73610.1%
 
72810.1%
 
69010.1%
 

Open.Porch.SF
Real number (ℝ≥0)

ZEROS

Distinct216
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46.335
Minimum0
Maximum742
Zeros901
Zeros (%)45.1%
Memory size15.6 KiB
2020-11-20T09:56:14.846001image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median25
Q372
95-th percentile172.05
Maximum742
Range742
Interquartile range (IQR)72

Descriptive statistics

Standard deviation65.68543265
Coefficient of variation (CV)1.417620215
Kurtosis13.19662385
Mean46.335
Median Absolute Deviation (MAD)25
Skewness2.640398016
Sum92670
Variance4314.576063
MonotocityNot monotonic
2020-11-20T09:56:15.043150image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
090145.1%
 
36341.7%
 
48311.6%
 
32301.5%
 
40281.4%
 
20251.2%
 
30251.2%
 
28251.2%
 
24231.1%
 
50221.1%
 
Other values (206)85642.8%
 
ValueCountFrequency (%) 
090145.1%
 
1020.1%
 
1120.1%
 
1240.2%
 
1510.1%
 
ValueCountFrequency (%) 
74210.1%
 
57010.1%
 
54710.1%
 
52310.1%
 
36810.1%
 

Enclosed.Porch
Real number (ℝ≥0)

ZEROS

Distinct147
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.9365
Minimum0
Maximum1012
Zeros1678
Zeros (%)83.9%
Memory size15.6 KiB
2020-11-20T09:56:15.246355image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile180
Maximum1012
Range1012
Interquartile range (IQR)0

Descriptive statistics

Standard deviation66.14438758
Coefficient of variation (CV)2.763327453
Kurtosis33.53035067
Mean23.9365
Median Absolute Deviation (MAD)0
Skewness4.264961216
Sum47873
Variance4375.080008
MonotocityNot monotonic
2020-11-20T09:56:15.452890image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0167883.9%
 
112150.8%
 
96110.5%
 
12090.4%
 
19290.4%
 
11680.4%
 
14480.4%
 
16880.4%
 
21660.3%
 
8460.3%
 
Other values (137)24212.1%
 
ValueCountFrequency (%) 
0167883.9%
 
1610.1%
 
1810.1%
 
2020.1%
 
2420.1%
 
ValueCountFrequency (%) 
101210.1%
 
58410.1%
 
55210.1%
 
42910.1%
 
36810.1%
 

X3Ssn.Porch
Real number (ℝ≥0)

ZEROS

Distinct20
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.116
Minimum0
Maximum320
Zeros1977
Zeros (%)98.9%
Memory size15.6 KiB
2020-11-20T09:56:15.628647image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum320
Range320
Interquartile range (IQR)0

Descriptive statistics

Standard deviation20.66811868
Coefficient of variation (CV)9.767541907
Kurtosis121.7957838
Mean2.116
Median Absolute Deviation (MAD)0
Skewness10.65770321
Sum4232
Variance427.1711296
MonotocityNot monotonic
2020-11-20T09:56:15.780971image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%) 
0197798.9%
 
16830.1%
 
21620.1%
 
18020.1%
 
15010.1%
 
8610.1%
 
9610.1%
 
12010.1%
 
13010.1%
 
14010.1%
 
Other values (10)100.5%
 
ValueCountFrequency (%) 
0197798.9%
 
8610.1%
 
9610.1%
 
12010.1%
 
13010.1%
 
ValueCountFrequency (%) 
32010.1%
 
30410.1%
 
29010.1%
 
24510.1%
 
23810.1%
 

Screen.Porch
Real number (ℝ≥0)

ZEROS

Distinct94
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.6815
Minimum0
Maximum480
Zeros1824
Zeros (%)91.2%
Memory size15.6 KiB
2020-11-20T09:56:15.963866image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile160
Maximum480
Range480
Interquartile range (IQR)0

Descriptive statistics

Standard deviation54.2705049
Coefficient of variation (CV)3.460798067
Kurtosis15.37807482
Mean15.6815
Median Absolute Deviation (MAD)0
Skewness3.777656524
Sum31363
Variance2945.287702
MonotocityNot monotonic
2020-11-20T09:56:16.170692image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0182491.2%
 
144120.6%
 
12090.4%
 
19280.4%
 
16870.4%
 
20060.3%
 
16050.2%
 
22450.2%
 
18040.2%
 
12640.2%
 
Other values (84)1165.8%
 
ValueCountFrequency (%) 
0182491.2%
 
4010.1%
 
6010.1%
 
6310.1%
 
6410.1%
 
ValueCountFrequency (%) 
48010.1%
 
44010.1%
 
39610.1%
 
38510.1%
 
37410.1%
 

Pool.Area
Real number (ℝ≥0)

ZEROS

Distinct12
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.934
Minimum0
Maximum800
Zeros1989
Zeros (%)99.5%
Memory size15.6 KiB
2020-11-20T09:56:16.348612image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum800
Range800
Interquartile range (IQR)0

Descriptive statistics

Standard deviation41.08082839
Coefficient of variation (CV)14.00164567
Kurtosis229.1033558
Mean2.934
Median Absolute Deviation (MAD)0
Skewness14.82245064
Sum5868
Variance1687.634461
MonotocityNot monotonic
2020-11-20T09:56:16.498351image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%) 
0198999.5%
 
80010.1%
 
73810.1%
 
64810.1%
 
57610.1%
 
55510.1%
 
51910.1%
 
51210.1%
 
48010.1%
 
44410.1%
 
Other values (2)20.1%
 
ValueCountFrequency (%) 
0198999.5%
 
22810.1%
 
36810.1%
 
44410.1%
 
48010.1%
 
ValueCountFrequency (%) 
80010.1%
 
73810.1%
 
64810.1%
 
57610.1%
 
55510.1%
 

Pool.QC
Categorical

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
None
1989 
Gd
 
4
Ex
 
3
TA
 
2
Fa
 
2
ValueCountFrequency (%) 
None198999.5%
 
Gd40.2%
 
Ex30.1%
 
TA20.1%
 
Fa20.1%
 
2020-11-20T09:56:16.690040image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-20T09:56:16.813523image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:56:16.976240image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length4
Mean length3.989
Min length2

Fence
Categorical

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
None
1605 
MnPrv
232 
GdWo
 
78
GdPrv
 
78
MnWw
 
7
ValueCountFrequency (%) 
None160580.2%
 
MnPrv23211.6%
 
GdWo783.9%
 
GdPrv783.9%
 
MnWw70.4%
 
2020-11-20T09:56:17.165451image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-20T09:56:17.290466image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:56:17.434329image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length5
Median length4
Mean length4.155
Min length4

Misc.Feature
Categorical

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
None
1926 
Shed
 
69
Othr
 
2
Gar2
 
2
TenC
 
1
ValueCountFrequency (%) 
None192696.3%
 
Shed693.5%
 
Othr20.1%
 
Gar220.1%
 
TenC10.1%
 
2020-11-20T09:56:17.618806image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-11-20T09:56:17.742420image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:56:17.893507image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length4
Mean length4
Min length4

Misc.Val
Real number (ℝ≥0)

SKEWED
ZEROS

Distinct31
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42.513
Minimum0
Maximum15500
Zeros1928
Zeros (%)96.4%
Memory size15.6 KiB
2020-11-20T09:56:18.053002image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum15500
Range15500
Interquartile range (IQR)0

Descriptive statistics

Standard deviation440.8310797
Coefficient of variation (CV)10.3693242
Kurtosis792.4045046
Mean42.513
Median Absolute Deviation (MAD)0
Skewness24.8772176
Sum85026
Variance194332.0409
MonotocityNot monotonic
2020-11-20T09:56:18.299072image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%) 
0192896.4%
 
400120.6%
 
500120.6%
 
60060.3%
 
45050.2%
 
200050.2%
 
70030.1%
 
250020.1%
 
65020.1%
 
150020.1%
 
Other values (21)231.1%
 
ValueCountFrequency (%) 
0192896.4%
 
5410.1%
 
8010.1%
 
30010.1%
 
35010.1%
 
ValueCountFrequency (%) 
1550010.1%
 
650010.1%
 
450020.1%
 
300010.1%
 
250020.1%
 

Mo.Sold
Real number (ℝ≥0)

Distinct12
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.2175
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Memory size15.6 KiB
2020-11-20T09:56:18.518445image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median6
Q38
95-th percentile11
Maximum12
Range11
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.726336407
Coefficient of variation (CV)0.4384939939
Kurtosis-0.4663181368
Mean6.2175
Median Absolute Deviation (MAD)2
Skewness0.1912928023
Sum12435
Variance7.432910205
MonotocityNot monotonic
2020-11-20T09:56:18.703063image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%) 
635217.6%
 
730115.0%
 
525412.7%
 
41949.7%
 
81618.1%
 
31618.1%
 
91165.8%
 
101135.7%
 
11974.9%
 
2934.7%
 
Other values (2)1587.9%
 
ValueCountFrequency (%) 
1844.2%
 
2934.7%
 
31618.1%
 
41949.7%
 
525412.7%
 
ValueCountFrequency (%) 
12743.7%
 
11974.9%
 
101135.7%
 
91165.8%
 
81618.1%
 

Yr.Sold
Real number (ℝ≥0)

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2007.7995
Minimum2006
Maximum2010
Zeros0
Zeros (%)0.0%
Memory size15.6 KiB
2020-11-20T09:56:18.856157image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum2006
5-th percentile2006
Q12007
median2008
Q32009
95-th percentile2010
Maximum2010
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.316117712
Coefficient of variation (CV)0.0006555025601
Kurtosis-1.162176397
Mean2007.7995
Median Absolute Deviation (MAD)1
Skewness0.1238567011
Sum4015599
Variance1.732165833
MonotocityNot monotonic
2020-11-20T09:56:19.171957image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
200747323.6%
 
200945022.5%
 
200842221.1%
 
200642221.1%
 
201023311.7%
 
ValueCountFrequency (%) 
200642221.1%
 
200747323.6%
 
200842221.1%
 
200945022.5%
 
201023311.7%
 
ValueCountFrequency (%) 
201023311.7%
 
200945022.5%
 
200842221.1%
 
200747323.6%
 
200642221.1%
 

Sale.Type
Categorical

Distinct10
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
WD
1738 
New
 
156
COD
 
64
ConLD
 
15
ConLI
 
9
Other values (5)
 
18
ValueCountFrequency (%) 
WD 173886.9%
 
New1567.8%
 
COD643.2%
 
ConLD150.8%
 
ConLI90.4%
 
CWD80.4%
 
ConLw40.2%
 
Oth30.1%
 
Con20.1%
 
VWD10.1%
 
2020-11-20T09:56:19.376666image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-11-20T09:56:19.514350image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:56:19.847876image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length5
Median length3
Mean length3.028
Min length3

Sale.Condition
Categorical

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
Normal
1640 
Partial
 
159
Abnorml
 
136
Family
 
33
Alloca
 
21
ValueCountFrequency (%) 
Normal164082.0%
 
Partial1598.0%
 
Abnorml1366.8%
 
Family331.7%
 
Alloca211.1%
 
AdjLand110.5%
 
2020-11-20T09:56:20.047017image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-20T09:56:20.182100image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:56:20.444129image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length7
Median length6
Mean length6.153
Min length6

SalePrice
Real number (ℝ≥0)

Distinct812
Distinct (%)40.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean180240.902
Minimum12789
Maximum755000
Zeros0
Zeros (%)0.0%
Memory size15.6 KiB
2020-11-20T09:56:20.660793image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum12789
5-th percentile88725
Q1129000
median160000
Q3213492.5
95-th percentile333209.6
Maximum755000
Range742211
Interquartile range (IQR)84492.5

Descriptive statistics

Standard deviation78461.92787
Coefficient of variation (CV)0.4353169952
Kurtosis5.353734438
Mean180240.902
Median Absolute Deviation (MAD)37000
Skewness1.738452639
Sum360481804
Variance6156274126
MonotocityNot monotonic
2020-11-20T09:56:20.856718image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
140000241.2%
 
135000231.1%
 
130000201.0%
 
160000190.9%
 
110000170.9%
 
155000160.8%
 
127000160.8%
 
145000160.8%
 
150000150.8%
 
115000150.8%
 
Other values (802)181991.0%
 
ValueCountFrequency (%) 
1278910.1%
 
3490010.1%
 
3500010.1%
 
3531110.1%
 
4500010.1%
 
ValueCountFrequency (%) 
75500010.1%
 
74500010.1%
 
61000010.1%
 
58450010.1%
 
58293310.1%
 

Interactions

2020-11-20T09:53:38.208153image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:53:38.407062image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:53:38.676192image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:53:38.831930image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:53:39.003365image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:53:39.170023image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:53:39.342876image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:53:39.546231image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:53:39.733506image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:53:39.937648image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:53:40.097192image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:53:40.304144image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:53:40.613688image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:53:40.852750image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:53:41.041029image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:53:41.229129image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:53:41.469737image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:53:41.633723image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:53:41.804820image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:53:41.972615image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:53:42.208575image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:53:42.395928image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:53:42.555031image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:53:42.756330image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:53:42.952786image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:53:43.147311image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:53:43.295468image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:53:43.532451image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:53:43.734842image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:53:43.986721image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:53:44.145008image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:53:44.295593image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:53:44.461352image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:53:44.706177image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:53:44.916308image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
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2020-11-20T09:55:07.910528image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:08.168433image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:08.330404image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:08.498391image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:08.656444image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:08.823152image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:08.992364image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:09.159524image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:09.327730image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:09.483371image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:09.668420image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:09.832387image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:10.010395image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:10.175699image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:10.342339image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:10.531710image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:10.709075image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:10.889226image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:11.126832image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:11.339272image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:11.527553image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:11.753469image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:11.998148image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:12.188018image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:12.421315image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:12.662842image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:12.833008image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:13.036867image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:13.281802image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:13.461531image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:13.692638image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:13.970261image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:14.233809image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:14.453892image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:14.643538image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:14.827990image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:15.105110image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:15.283131image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:15.457557image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:15.701823image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:15.955759image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:16.143363image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:16.362016image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:16.590180image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:16.777052image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:16.956545image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:17.151774image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:17.348477image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:17.519069image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:17.708313image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:17.878267image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:18.069410image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:18.325786image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:18.542867image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:19.134650image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:19.337024image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:19.529756image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:19.715465image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:19.902212image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:20.088325image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:20.248584image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:20.398396image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:20.546918image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:20.713186image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:20.872714image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:21.032817image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:21.178893image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:21.328006image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:21.491354image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:21.642027image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:21.809244image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:21.973802image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:22.127025image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:22.293498image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:22.442604image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:22.604726image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:22.759225image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:22.916718image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:23.072195image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:23.242359image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:23.408694image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:23.560345image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:23.730198image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:23.895840image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:24.125518image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:24.434690image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:24.633412image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:24.828717image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:25.010979image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:25.203889image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:25.393024image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:25.567357image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:25.753272image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:25.931546image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:26.154258image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:26.420483image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:26.604031image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:26.809810image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:26.994114image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:27.183054image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:27.432515image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:27.745356image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:27.936700image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:28.171487image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:28.500574image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:28.761257image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:29.048427image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:29.246935image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:29.457141image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:29.728098image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:29.911895image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:30.107392image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:30.290661image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:30.473837image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:30.727346image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:30.992040image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:31.181712image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:31.350513image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:31.535595image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:31.775586image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:32.064695image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:32.254245image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:32.481385image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:32.793904image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:33.064905image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:33.317006image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:33.507762image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:33.700657image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:33.893886image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:34.066195image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:34.256683image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Correlations

2020-11-20T09:56:21.091151image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-11-20T09:56:21.561946image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-11-20T09:56:21.993839image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-11-20T09:56:22.554157image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2020-11-20T09:56:24.620885image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2020-11-20T09:55:35.003085image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:42.527668image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:44.510419image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-20T09:55:44.925744image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Sample

First rows

MS.SubClassMS.ZoningLot.FrontageLot.AreaStreetAlleyLot.ShapeLand.ContourUtilitiesLot.ConfigLand.SlopeNeighborhoodCondition.1Condition.2Bldg.TypeHouse.StyleOverall.QualOverall.CondYear.BuiltYear.Remod.AddRoof.StyleRoof.MatlExterior.1stExterior.2ndMas.Vnr.TypeMas.Vnr.AreaExter.QualExter.CondFoundationBsmt.QualBsmt.CondBsmt.ExposureBsmtFin.Type.1BsmtFin.SF.1BsmtFin.Type.2BsmtFin.SF.2Bsmt.Unf.SFTotal.Bsmt.SFHeatingHeating.QCCentral.AirElectricalX1st.Flr.SFX2nd.Flr.SFLow.Qual.Fin.SFGr.Liv.AreaBsmt.Full.BathBsmt.Half.BathFull.BathHalf.BathBedroom.AbvGrKitchen.AbvGrKitchen.QualTotRms.AbvGrdFunctionalFireplacesFireplace.QuGarage.TypeGarage.Yr.BltGarage.FinishGarage.CarsGarage.AreaGarage.QualGarage.CondPaved.DriveWood.Deck.SFOpen.Porch.SFEnclosed.PorchX3Ssn.PorchScreen.PorchPool.AreaPool.QCFenceMisc.FeatureMisc.ValMo.SoldYr.SoldSale.TypeSale.ConditionSalePrice
0120RL343901PaveNoneRegLvlAllPubInsideGtlNridgHtNormNormTwnhs1Story6520052006GableCompShgVinylSdVinylSdStone182GdTAPConcGdTAAvALQ866Unf04361302GasAExYSBrkr1302001302101111Gd5Typ1GdAttchd2005RFn2631TATAY110500000NoneNoneNone082007NewPartial204000
120RL708400PaveNoneRegLvlAllPubCornerGtlNonemesNormNorm1Fam1Story4519701970GableCompShgPlywoodPlywoodNone0TATACBlockTATANoALQ804Rec780882GasATAYSBrkr88200882101021TA4Typ0NoneAttchd1970Fin2525TATAY24000000NoneMnPrvNone042010WDNormal126000
285RL607200PaveNoneRegLvlAllPubInsideGtlCollgCrNormNorm1FamSFoyer5819722003GableCompShgWdShingHdBoardNone0TAGdCBlockGdTAAvGLQ660Unf0108768GasAGdYSBrkr76800768011021TA5Typ0NoneDetchd1974Fin1396TATAY19200000NoneMnPrvNone042009WDNormal133900
390RL647018PaveNoneRegBnkAllPubInsideGtlSawyerWNormNormDuplex1Story5519791979GableCompShgPlywoodPlywoodNone0TATASlabNoneNoneNoneNone0None000GasATAYSBrkr1535001535002042TA8Typ0NoneAttchd1979Unf2400TATAY000000NoneNoneNone062009WDAlloca118858
460RL11116259PaveNoneRegLvlAllPubCornerGtlNridgHtNormNorm1Fam2Story9520062006GableCompShgVinylSdVinylSdStone370TATAPConcExGdAvUnf0Unf012491249GasAExYSBrkr1249134702596003141Gd9Typ0NoneAttchd2006RFn3840TATAY2401540000NoneNoneNone092006NewPartial342643
520RL504280PaveNoneIR1LvlAllPubInsideGtlSawyerNormNorm1Fam1Story4919462001GableCompShgMetalSdMetalSdNone0TAGdCBlockFaTANoUnf0Unf0560560GasAExYFuseA70400704011021Fa4Typ0NoneCarPort1946Unf1220TATAY0024000NoneNoneNone092009WDNormal88750
620RL15520064PaveNoneIR1LowAllPubInsideSevClearCrNormNorm1Fam1Story8619761976ShedWdShnglWd SdngWd SdngNone0GdTACBlockGdGdGdLwQ51GLQ9150966GasAExYSBrkr1743001743200101Gd5Typ2FaAttchd1976Fin2529TATAY64600000NoneNoneNone052007WDNormal279000
720RM607200PaveGrvlRegLvlAllPubInsideGtlOldTownNormNorm1Fam1Story4519501950GableCompShgMetalSdMetalSdNone0TATACBlockTATANoUnf0Unf0576576GasAExYSBrkr86400864001021TA5Typ0NoneDetchd1952RFn1528TATAY00001150NoneNoneNone082006CODNormal105000
820RL709100PaveNoneRegLvlAllPubInsideGtlCollgCrNormNorm1Fam1Story7520002000GableCompShgVinylSdVinylSdBrkFace244GdTAPConcGdTAAvGLQ1400Unf01251525GasAExYSBrkr1525001525102031Gd6Typ0NoneAttchd2000RFn2541TATAY219360000NoneNoneNone092006WDNormal235000
970C (all)None6449PaveNoneIR1LvlAllPubInsideGtlSWISUNormNorm1Fam2Story4119071950GambrelCompShgWd SdngStuccoNone0TATACBlockTATANoRec73Unf0634707GasWTANSBrkr94294201884001141TA7Typ0NoneNoneNoneNone00NoneNoneN00239000NoneNoneNone032010WDAbnorml93369

Last rows

MS.SubClassMS.ZoningLot.FrontageLot.AreaStreetAlleyLot.ShapeLand.ContourUtilitiesLot.ConfigLand.SlopeNeighborhoodCondition.1Condition.2Bldg.TypeHouse.StyleOverall.QualOverall.CondYear.BuiltYear.Remod.AddRoof.StyleRoof.MatlExterior.1stExterior.2ndMas.Vnr.TypeMas.Vnr.AreaExter.QualExter.CondFoundationBsmt.QualBsmt.CondBsmt.ExposureBsmtFin.Type.1BsmtFin.SF.1BsmtFin.Type.2BsmtFin.SF.2Bsmt.Unf.SFTotal.Bsmt.SFHeatingHeating.QCCentral.AirElectricalX1st.Flr.SFX2nd.Flr.SFLow.Qual.Fin.SFGr.Liv.AreaBsmt.Full.BathBsmt.Half.BathFull.BathHalf.BathBedroom.AbvGrKitchen.AbvGrKitchen.QualTotRms.AbvGrdFunctionalFireplacesFireplace.QuGarage.TypeGarage.Yr.BltGarage.FinishGarage.CarsGarage.AreaGarage.QualGarage.CondPaved.DriveWood.Deck.SFOpen.Porch.SFEnclosed.PorchX3Ssn.PorchScreen.PorchPool.AreaPool.QCFenceMisc.FeatureMisc.ValMo.SoldYr.SoldSale.TypeSale.ConditionSalePrice
199080RL8511475PaveNoneRegLvlAllPubCornerGtlNonemesNormNorm1FamSLvl6619611961HipCompShgHdBoardHdBoardBrkFace90TATACBlockTATAGdALQ568Unf06401208GasAExYSBrkr1576001576101041Gd7Typ1PoBuiltIn1961Fin2368TATAY8500000NoneNoneNone092009WDNormal174500
199120RL10713891PaveNoneRegLvlAllPubInsideGtlNridgHtNormNorm1Fam1Story9520072007HipCompShgVinylSdVinylSdStone456ExTAPConcExTAGdGLQ1812Unf07402552GasAExYSBrkr2552002552102031Ex8Typ2ExAttchd2007Fin3932TATAY130280000NoneNoneNone0102007NewPartial479069
199220RL8514082PaveNoneIR1HLSAllPubInsideGtlStoneBrNormNorm1Fam1Story8520062006HipCompShgVinylSdVinylSdBrkFace945GdTAPConcExGdGdGLQ1558Unf06622220GasAExYSBrkr2234002234101111Gd7Typ1GdAttchd2006RFn2724TATAY390800000NoneNoneNone012007WDNormal441929
199320RL6514753PaveNoneIR2LowAllPubInsideGtlCollgCrPosNNorm1Fam1Story7519981998GableCompShgVinylSdVinylSdNone0TATAPConcGdTAMnGLQ950Unf05131463GasAExYSBrkr1463001463102031TA5Typ0NoneAttchd1998Fin2539TATAY0810000NoneGdPrvNone0122009WDNormal207000
199420RL8710367PaveNoneIR1LvlAllPubInsideGtlNridgHtNormNorm1Fam1Story9520082008HipCompShgVinylSdVinylSdStone284ExTAPConcExTAMnGLQ1015Unf07241739GasAExYSBrkr1743001743102031Ex8Typ1GdAttchd2008RFn3927TATAY168450000NoneNoneNone062009ConLINormal335000
199580RL808000PaveNoneRegLvlAllPubInsideGtlNonemesNormNorm1FamSLvl5519591959GableCompShgBrkFacePlywoodNone0TATACBlockGdTAAvGLQ433Rec950528GasATAYSBrkr1183001183101031TA6Typ0NoneAttchd1959RFn1288TATAY000000NoneGdWoNone072009WDNormal138000
1996180RM353675PaveNoneRegLvlAllPubInsideGtlEdwardsNormNormTwnhsESLvl6520052005GableCompShgVinylSdVinylSdBrkFace80TATAPConcGdTAGdGLQ459Unf088547GasAExYSBrkr1072001072101021TA5Typ0NoneBasment2005RFn2525TATAY0280000NoneNoneNone062008WDNormal148000
199760RL7610142PaveNoneIR1LvlAllPubInsideGtlSawyerWNormNorm1Fam2Story7520042004GableCompShgVinylSdVinylSdNone0GdTAPConcGdTANoGLQ656Unf0300956GasAExYSBrkr956112802084102141Gd8Typ0NoneBuiltIn2004RFn2618TATAY0450000NoneNoneNone012010WDNormal233000
199885RLNone7252PaveNoneIR1LvlAllPubCulDSacGtlSawyerNormNorm1FamSFoyer5519821982HipCompShgWd SdngWd SdngNone0TATACBlockGdTAAvGLQ685Unf0173858GasATAYSBrkr85800858101021TA5Typ0NoneDetchd1983Unf2576TATAY12000000NoneNoneNone042009WDNormal134900
1999160FV342998PaveNoneRegLvlAllPubInsideGtlSomerstNormNormTwnhsE2Story6520002000GableCompShgMetalSdMetalSdBrkFace513GdTAPConcGdTANoGLQ507Unf0249756GasAExYSBrkr75675601512102121Gd4Typ0NoneDetchd2000Unf2440TATAY0320000NoneNoneNone082009WDNormal180000